Nature Communications (Oct 2021)
Stroboscopic operando spectroscopy of the dynamics in heterogeneous catalysis by event-averaging
- Jan Knudsen,
- Tamires Gallo,
- Virgínia Boix,
- Marie Døvre Strømsheim,
- Giulio D’Acunto,
- Christopher Goodwin,
- Harald Wallander,
- Suyun Zhu,
- Markus Soldemo,
- Patrick Lömker,
- Filippo Cavalca,
- Mattia Scardamaglia,
- David Degerman,
- Anders Nilsson,
- Peter Amann,
- Andrey Shavorskiy,
- Joachim Schnadt
Affiliations
- Jan Knudsen
- Division of Synchrotron Radiation Research, Department of Physics, Lund University
- Tamires Gallo
- Division of Synchrotron Radiation Research, Department of Physics, Lund University
- Virgínia Boix
- Division of Synchrotron Radiation Research, Department of Physics, Lund University
- Marie Døvre Strømsheim
- Department of Chemical Engineering, Norwegian University of Science and Technology (NTNU)
- Giulio D’Acunto
- Division of Synchrotron Radiation Research, Department of Physics, Lund University
- Christopher Goodwin
- Department of Physics, Stockholm University
- Harald Wallander
- Division of Synchrotron Radiation Research, Department of Physics, Lund University
- Suyun Zhu
- MAX IV Laboratory, Lund University
- Markus Soldemo
- Department of Physics, Stockholm University
- Patrick Lömker
- Deutsches Elektronen-Synchrotron DESY
- Filippo Cavalca
- MAX IV Laboratory, Lund University
- Mattia Scardamaglia
- MAX IV Laboratory, Lund University
- David Degerman
- Department of Physics, Stockholm University
- Anders Nilsson
- Department of Physics, Stockholm University
- Peter Amann
- Department of Physics, Stockholm University
- Andrey Shavorskiy
- MAX IV Laboratory, Lund University
- Joachim Schnadt
- Division of Synchrotron Radiation Research, Department of Physics, Lund University
- DOI
- https://doi.org/10.1038/s41467-021-26372-y
- Journal volume & issue
-
Vol. 12,
no. 1
pp. 1 – 8
Abstract
To follow in situ and in real time how catalyst surfaces respond to gas composition changes is a challenge. This study reports on an eventaveraging method, based on cyclic gas pulsing and software-based image recognition, that overcomes the challenge for large photoelectron spectroscopy datasets.
